3
Approaches to Vulnerability Assessments

INTRODUCTION

Numerous approaches have been used or proposed for assessing ground water vulnerability. They range from sophisticated models of the physical, chemical, and biological processes occurring in the vadose zone and ground water regime, to models that weight critical factors affecting vulnerability through either statistical methods or expert judgment. Each of these categories of techniques are reviewed in this chapter, with particular emphasis on their strengths and limitations.

A fundamental characteristic of all approaches to vulnerability assessment is uncertainty, either in the method itself or in the data it uses. These uncertainties are discussed, and ways to analyze and minimize them are presented. Possibilities for testing and evaluating models are discussed for both field-scale and regional-scale assessments. At the conclusion of this chapter, geographic information systems (GIS) are presented as a commonly used computing environment for executing some types of assessments and for displaying the results of virtually all types of assessments.

The potential for contaminants to leach to ground water depends on many factors, including the composition of the soils and geologic materials in the unsaturated zone, the depth to the water table, the recharge rate, and environmental influences on the potential for biodegradation. The composition of the unsaturated zone can greatly influence transformations and reactions. For example, high organic matter or clay content increases sorption



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty 3 Approaches to Vulnerability Assessments INTRODUCTION Numerous approaches have been used or proposed for assessing ground water vulnerability. They range from sophisticated models of the physical, chemical, and biological processes occurring in the vadose zone and ground water regime, to models that weight critical factors affecting vulnerability through either statistical methods or expert judgment. Each of these categories of techniques are reviewed in this chapter, with particular emphasis on their strengths and limitations. A fundamental characteristic of all approaches to vulnerability assessment is uncertainty, either in the method itself or in the data it uses. These uncertainties are discussed, and ways to analyze and minimize them are presented. Possibilities for testing and evaluating models are discussed for both field-scale and regional-scale assessments. At the conclusion of this chapter, geographic information systems (GIS) are presented as a commonly used computing environment for executing some types of assessments and for displaying the results of virtually all types of assessments. The potential for contaminants to leach to ground water depends on many factors, including the composition of the soils and geologic materials in the unsaturated zone, the depth to the water table, the recharge rate, and environmental influences on the potential for biodegradation. The composition of the unsaturated zone can greatly influence transformations and reactions. For example, high organic matter or clay content increases sorption

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty and thus lessens the potential for contamination. The depth to the water table can be important because short flow paths decrease the opportunity for sorption and biodegradation and thus increase the potential for contamination. Conversely, longer flow paths from land surface to the water table can lessen the potential for contamination by chemicals that sorb or degrade along the flowpath. The recharge rate is important because it affects the extent and rate of transport of contaminants through the unsaturated zone. Finally, environmental factors, such as temperature and water content, can significantly influence the loss of contaminants by microbial transformations. Some general geologic and hydrologic factors that influence an aquifer's vulnerability to contamination are shown in Table 3.1, along with examples of features that lead to low or high vulnerability. Although these factors may seem quite simple at first inspection, many of them interact in the TABLE 3.1 Principal Geologic and Hydrologic Features that Influence an Aquifer's Vulnerability to Contamination (After Johnston 1988) Feature Determining Aquifer Vulnerability to Contamination Low Vulnerability High Vulnerability A. Hydrogeologic Framework Unsaturated Zone Thick unsaturated zone, with high levels of clay and organic materials. Thin unsaturated zone, with high levels of sand, gravel, limestone, or basalt of high permeability. Confining Unit Thick confining unit of clay or shale above aquifer. No confining unit. Aquifer Properties Silty sandstone or shaley limestone of low permeability. Cavernous limestone, sand and gravel, gravel, or basalt of high permeability. B. Ground Water Flow System Recharge Rate Negligible recharge rate, as in arid regions. Large recharge rate, as in humid regions. Location within flow system (proximity to recharge or discharge area) Located in the deep, sluggish part of a regional flow system. Located within a recharge area or within the cone of depression of a pumped well.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty TABLE 3.2 A Listing of Some Key Parameters in Models of Pesticide Transport in Soils (Adapted from Wagenet and Rao 1990. Reprinted, by permission, from the Soil Science Society of America, 1990.) Pesticide Parameters Organic carbon-normalized sorption coefficient (Koc) Distribution coefficient (Kd) Aqueous solubility Henry's constant Saturated vapor density Gas phase diffusion coefficient Biological half-life Hydrolysis half-life Oxidation half-life Foliar decay rate Soil Parameters Dispersion coefficient Saturated water content Field-capacity water content (θFC) Wilting-point water content Hydraulic properties Bulk density (ρb) Organic carbon content (foc) pH Cation exchange capacity Heat flow parameters Crop Parameters Root density distribution Maximum rooting depth Pesticide uptake rates Climatological Parameters Rainfall or irrigation rates Pan evaporation rates Daily maximum and minimum temperature Snow melt Hours of sunlight Management Parameters Pesticide application rate and timing Pesticide application method and formulation Crop production-system variables Soil-management variables environment to create more complex and subtle distinctions in vulnerability than the extreme situations in Table 3.1. Furthermore, many of these factors affecting vulnerability are highly variable and difficult to characterize over any given area. One set of characterizations is shown in Table 3.2, which lists some of the key parameters often used in modeling one aspect of ground water contamination potential, pesticide transport and transformation in soils. REVIEW OF CURRENT APPROACHES Combinations of some or all of the factors noted above are included in the various approaches used to assess ground water vulnerability. These approaches range in complexity from a subjective evaluation of available map data to the application of complex contaminant transport models. The U.S. Environmental Protection Agency (EPA 1992a) evaluated the methods

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty currently available for assessing aquifer sensitivity or ground water vulnerability to pesticide contamination. Their categorization includes three broad classes of approaches depending on the factors included in the assessment method. Each class is broken down further into specific types of approaches, such as aquifer sensitivity assessment methods which consider only hydrogeologic factors; hybrid methods, which consider hydrogeologic and pesticide factors; and ground water vulnerability assessment methods, which consider hydrogeologic, pesticide, and agronomic factors. Statistical tools are also noted for their usefulness in validating methods or providing hydrogeologic setting information. Our alternative classification scheme places assessment methods in three general categories: (1) overlay and index methods, (2) methods employing process-based simulation models, and (3) statistical methods. Assessment methods in the first category, overlay and index methods, are based on combining maps of various physiographic attributes (e.g., geology, soils, depth to water table) of the region by assigning a numerical index or score to each attribute. In the simplest of these methods, all attributes are assigned equal weights, with no judgment being made on their relative importance. Thus, areas where simple confluence of the specified attributes occurs (e.g., sandy soils and shallow ground water) are deemed vulnerable. Such methods were the earliest to be used and are still favored by many state and local regulatory and planning agencies. Overlay and index methods that attempt to be more quantitative assign different numerical scores and weights to the attributes in developing a range of vulnerability classes, which are then displayed on a map. Popularization of GIS technology has made it increasingly easy to adopt map overlay and index methods. The assessment methods in the second category, methods employing process-based simulation models, require analytical or numerical solutions to mathematical equations that represent coupled processes governing contaminant transport. Methods in this category range from indices based on simple transport models to analytical solutions for one-dimensional transport of contaminants through the unsaturated zone to coupled, unsaturated-saturated, multiple phase, two- or three-dimensional models. Statistical methods having a contaminant concentration or a probability of contamination as the dependent variable form the basis for the third category. These methods incorporate data on known areal contaminant distributions and provide characterizations of contamination potential for the specific geographic area from which data were drawn. Statistical methods are sometimes used by regulatory agencies that have the regional databases on ground water contamination needed to develop models. Some characteristics of selected vulnerability assessment methods used in the United States are listed in Table 3.3. Comparative details on these

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty TABLE 3.3 Selected Methods Used in the United States to Evaluate Ground Water Vulnerability to Contamination Method Reference Map Scale1 Reference Location Intrinsic and/or Specific Overlay and Index Methods Kansas Leachability Index Kissel et al. 1982 Small Soil Intrinsic DRASTIC Aller et al. 1985, 1987 Variable Ground Water Intrinsic California Hotspots Cohen et al. 1986 Large Water Table Intrinsic and Specific Washington Map Overlay Vulnerability Sacha et al. 1987 Small Ground Water Intrinsic and Specific SEEPPAGE Moore 1988 Variable Ground Water Intrinsic Iowa Ground Water Vulnerability Hoyer and Hallberg 1991 Small Ground Water Intrinsic EPA/UIC Pettyjohn et al. 1991 Small Ground Water Intrinsic

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Process-Based Simulation Models PESTANS Enfield et al. 1982 Large Soil Specific BAM Jury et al. 1983 Large Soil Specific MOUSE Steenhuis et al. 1987 Large Ground Water Specific PRZM Carsel et al. 1984 Large Soil Specific RF/AF Rao et al. 1985 Variable Soil Specific GLEAMS Leonard et al. 1987 Large Soil Specific CMLS Nofziger and Hornsby 1986 Large Soil Specific RITZ/VIP McLean et al. 1988 Large Soil Specific LEACHM Wagenet and Hutson 1987 Large Soil Specific RUSTIC Dean et al. 1989 Large Ground Water Specific and Intrinsic Statistical Methods Discriminant Analysis Teso et al. 1988 Small Ground Water Specific Regression Analysis Chen and Druliner 1988 Small Ground Water Specific 1 "Large scale" means that the method is typically applied at a level of detail of at least a 1:24,000 scale map to a small spatial area; "small scale" means that the method is typically applied at a level of detail less than that of a 1:50,000 scale map to a larger spatial area.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty and other methods were published recently by EPA (1992a). Inspection of Table 3.3 reveals some general similarities within the broad classes of methods. Overlay and index methods tend to be applied at small map scales (large study areas), typically greater than 1:50,000, whereas most current process-based models apply to problems at much larger map scales (smaller study areas). Most overlay and index methods and most statistical methods refer to the saturated zone (the ground water resource) or water table as the reference location. In contrast, most process-based models have a floating reference location depending on the extent to which contamination is investigated through the vadose zone (for example, the reference location may be the bottom of the crop root zone for agricultural scenarios). Most overlay and index methods are designed to evaluate intrinsic vulnerability or have mixed specific and intrinsic utility. In contrast, most process-based models and statistical methods are designed for specific classes of contaminants such as pesticides or nitrate. Overlay and Index Methods Overlay and index methods rely primarily on qualitative or semiquantitative compilations and interpretations of mapped data. Selected overlay and index methods are listed in Table 3.4 together with the parameters used in their application. Additional methods are summarized by the U.S. Environmental Protection Agency (1992a). Variables used in the overlay and index methods typically include approximate depth to the water table, ground water recharge rate, and soil and aquifer material properties. Depth to Ground Water The shorter the distance to ground water, the less soil and underlying unsaturated zone material is there to act as a filter or adsorbent. Depth to ground water also affects the transit time available for various abiotic and biotic processes to degrade the chemical. Depth to ground water corresponds to the depth to water table in unconfined aquifers or to the depth to the bottom of a confining geologic unit when the uppermost aquifer is confined. Varying degrees of confinement over an area are common. Overlay and index methods use a single depth to ground water at each location. However, large seasonal fluctuations in water levels in unconfined aquifers can complicate the estimate of single representative values. Seasonally high water table depths may be used to provide conservative estimates. Information on the depth to ground water is available from many sources, including well logs, federal and state agency computer files, and water-level maps published by federal and state agencies, universities, and consulting firms.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty TABLE 3.4 Parameters Used in Selected Overlay and Index Methods for Vulnerability Assessments Parameters Related to Method Author(s) Depth to Ground Water Recharge Unsaturated Zone and Aquifer Material Other DRASTIC Aller et al. 1985 Aller et al. 1987 Depth to water table Net recharge Soil media Vadose zone media Aquifer media Hydraulic conductivity Slope Wisconsin Ground Water Contamination Susceptibility Wisconsin Department of Natural Resources, Wisconsin Geological and Natural History Survey 1987 Depth to water table — Soil characteristics (4 classes based on texture) surficial deposits Depth to bedrock Bedrock type — Potential for Contamination of Shallow Aquifers in Illinois by Agricultural Chemicals Berg and Kempton 1988; McKenna and Keefer 1991 — — Soils and geologic materials differentiated by thickness, texture, permeability, and stratigraphic position — Ground Water Vulnerability Regions of Iowa Hoyer and Hallberg 1991 Depth to private well water sources — Aquifer type (alluvial, bedrock, glacial drift) and thickness of confinement by low permeability drift or shale Locations of sinkholes and agricultural drainage wells State-by-State Assessment of Aquifer Vulnerability and Sensitivity for the Conterminous U.S. Pettyjohn et al. 1991 — — Geologically based classification of surficial and relatively shallow aquifers —

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Recharge Estimates of ground water recharge used in vulnerability assessments should account for all inputs (e.g., rainfall, irrigation, artificial recharge, and wastewater applications) and losses (e.g., runoff, evapotranspiration) of water. Typically, average annual values of recharge are used, and recharge is assumed to be uniform over large areas. In reality, recharge is commonly quite variable in time, both seasonally and annually, and it can be highly variable over a region. The identification of recharge and discharge zones may be particularly useful in assessing the potential for contaminants introduced at the water table to move deeper into the ground water system. Evaluating recharge and discharge zones can be difficult in hydrogeologic systems where ground water flow systems occur at different scales. For instance, a given area may have local flow systems with discharge zones within hundreds of meters of the recharge zones, intermediate-scale systems of one or a few kilometers that encompass two or more local flow systems, and regional-scale flow systems many kilometers long that begin at the major ground water system divide and traverse the entire regional system to the major drain. The extent to which flow systems of different spatial scales can be defined as parts of regional assessments of ground water vulnerability is subject to significant limitations. Nonetheless, the identification of recharge and discharge zones may be one of the more important elements of a vulnerability assessment. Properties of the Unsaturated Zone and Aquifer Material Many different properties of the unsaturated zone and aquifer material may be incorporated into overlay and index methods. Ideally, one might consider properties of the unsaturated zone to indicate the potential for vertical transport of contaminants to ground water, while properties of the aquifer indicate the potential for lateral transport. Because the aquifer material commonly is also part of the unsaturated zone, such a clear distinction does not always exist in application of overlay and index methods. In fact, for many overlay and index methods, it is not always obvious whether the reference location is the water table or some unspecified location within the ground water flow system. Properties of the unsaturated zone and aquifer material listed in Table 3.4 illustrate considerable diversity among vulnerability assessment methods. Many of the methods consider geology, but neglect soils, others focus on soils, but ignore geology. Some indexing methods, like DRASTIC, attempt to be universally applicable and incorporate parameters that should be available to some degree virtually everywhere; other methods are adjusted

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty to the setting and data bases available in a particular area. An advantage of the latter approach is that geologic and geographic features unique to a particular area can be taken into account. For example, the Illinois method (Berg and Kempton 1988, McKenna and Keefer 1991) involved an intensive examination of stratigraphy and the identification of low and high permeability units in a three-dimensional context throughout the state. Finally, in addition to the foregoing factors related to hydrology, geology, and soils, some overlay and index methods have combined use of these factors with surrogate data on contaminant loading. For example, Moreau and Danielson (1990) used DRASTIC scores in combination with estimated pesticide use rates to produce vulnerability maps for selected pesticides for the state of North Carolina. Major sources of data used in overlay and index methods include: 1) soil maps generated by the Soil Conservation Service (SCS) in conjunction with state and local agencies, 2) topographic maps produced by the U.S. Geological Survey (USGS), 3) geologic maps published by the USGS, state geological surveys, and other sources, and 4) regional and local land-use planning maps. Discussion A simple overlay-type vulnerability map is prepared by superposing a series of maps showing the areal distributions of attributes considered important in characterizing the potential for ground water contamination (e.g., soil types, depth to ground water, recharge rate). Each attribute is given equal weight, and areas with different vulnerability ratings are defined by the patterns or ranges of attribute values that overlap in the area. Typically, the product is a single map depicting areas of differing vulnerability, designated by a score, pattern, or color. In some instances, overlay methods identify areas with different expected ground water vulnerabilities, but no attempt is made to rank the areas from most to least vulnerable. Perhaps the simplest overlay method is that used by Pettyjohn et al. (1991) for evaluating the potential for ground water contamination in the contiguous United States on a state-by-state basis. They developed their method specifically for the U.S. EPA's Underground Injection Control Program, but indicated that "the products are equally valuable to assess the potential for ground water contamination from other surface or near surface sources." Their vulnerability assessment is based solely on a geologic classification of surficial and relatively shallow aquifers. Pettyjohn et al. (1991) also evaluated aquifer sensitivity in which they included population density as an additional factor. Overlay methods are commonly used for vulnerability assessments at

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty the state level. For example, Illinois (Berg and Kempton 1988, McKenna and Keefer 1991) and Iowa (Hoyer and Hallberg 1991) have developed GIS-based maps using overlay methods with an emphasis on geology as the key attribute for assessing vulnerability. An overlay map for the state of Wisconsin considers depth to water, geology, and soils information (Wisconsin Department of Natural Resources and Wisconsin Geological and Natural History Survey 1987). In contrast to simple overlay methods, index methods assign a numerical value to each attribute based on its magnitude or qualitative ranking. Each attribute, in turn, is assigned a relative importance or weight compared to the other attributes. A consensus of experts may be solicited (the Delphi approach) to determine the relative weights assigned to different attributes and the numerical values assigned to different levels of each attribute. The weighted-attribute ratings are summed to obtain an overall numerical score for ground water vulnerability. These numerical scores are used to group similar areas into classes or categories of vulnerability (e.g., low, medium, and high) that are then displayed on a map. Some methods multiply the numerical scores or values assigned to the attributes together rather than adding them (c.f., Back et al. 1984). Several types of indices have been developed for ground water vulnerability assessments. The DRASTIC index (Aller et al. 1987) is perhaps the best known of these methods. Some state regulatory agencies have developed index assessment methods similar to DRASTIC (cf., Rupert et al. 1991). Using information about pesticide leaching abilities, Kellogg et al. (1992) developed the GWVIP and GWVIN indices to generate national-scale vulnerability maps for pesticides and nitrates, respectively (see Chapter 5). Overlay and index methods have often been developed with the availability of information keenly in mind. These methods are driven largely by data availability and expert judgment, with less emphasis on processes controlling ground water contamination. One can argue whether the factors included in the methods are the relevant ones for vulnerability assessment and whether the factor ratings are appropriate. For example, Banton and Villeneuve (1989) questioned the basis for the numerical weighting scheme used by Agricultural DRASTIC after comparing its results with those from a process-based modeling approach (PRZM). Further, Holden et al. (1992) concluded that "the complex weighting and coding procedures used in the DRASTIC scoring are self defeating," and that in the short-term, "simpler classification schemes, focusing on only a few major vulnerability factors, look to be more useful than DRASTIC." There are no quantitative criteria for evaluating the scientific basis of these methods. Many overlay and index methods address intrinsic vulnerability, although some of them address what might be called pseudospecific vulnerability.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty loss in tons per acre as a product of factors representing climate (R), soil erodibility (K), topography (LS), vegetative cover (C), and supporting conservation practices (P). Actual soil loss (A) can be computed by the equation: For each of these factors, an intermediate map layer is generated using GIS. Some of these maps are created by simply regrouping the classes on another map (e.g., soil mapping units on a soils map are regrouped into classes of erodibility to create an erodibility factor map). Maps for other factors are created by applying mathematical formulae between map layers. For example, the topography factor (LS) is computed from the steepness of slope (S) and the length of the slope (L), with the formula: where, = slope length in feet; = angle of slope; and m = 0.5 if the percent slope is 5 or more, 0.4 on slopes of 3.5 to 4.5 percent, 0.3 on slopes of 1 to 3 percent, and 0.2 on uniform gradients of less than 1 percent. Such equations can be solved with generic GIS tools, using the map layers to supply the variables. Likewise, to create a map of soil loss using GIS, the intermediate maps representing the five USLE factors are simply multiplied together, resulting in a map of estimated soil loss as well as the associated statistical data. In these examples, the computations are applied across the map, with the equations applied independently for each point on the map. Although the concept of adding two maps or multiplying several maps may seem unusual, this is a routine capability of GIS technology and is duplicated in most non-GIS based approaches that attempt to deal with the spatial distribution of simple models like USLE. New GIS functions and developments in related technologies have resulted in the ability to model environmental factors in a more sophisticated manner. Examples of these functions are: Diffusion functions can be used to depict the migration of entities across surfaces based on attributes of those surfaces. N-dimensional queries allow the user to interrogate the database for attribute information from multiple data layers at the same time, which is very useful in data visualization and model validation. Neighborhood analysis develops information on the adjacency, size, and geometry of physical features to further model them and their relationship to other features. Direct linkages between databases and software facilitate transfer of

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty up-to-date information among applications, which promotes collaboration rather than duplication of efforts among supporting technologies. Software programs can transform an arduous set of commands into a simple procedure, thus providing sophisticated analyses to GIS novices. Many GIS environments, however, still lack some of the basic analytical capabilities needed by modelers. For example, GIS analytical functions use static information and are run on demand. The dynamic nature of environmental phenomena is lost by these static models. Additionally, most GIS techniques today work only in two dimensions, which makes it difficult to visualize the relationships among surface and subsurface features. Some of these problems may be solved by software developments and should be reevaluated over time. GIS technology can be used beneficially in ground water vulnerability assessments by supplying tools for encoding and producing geographic and attribute data, by computing spatial and attribute relationships, and by graphically portraying these relationships and model output. The technology can also be particularly useful to overlay and index methods by allowing various data layers to be integrated and/or weighted. Since GIS technology is designed to be adaptable to different technical and procedural requirements of vulnerability assessments, developments in the field can be expected to strengthen the support GIS can offer other assessment approaches. SUMMARY The methods used to assess ground water vulnerability range from simple overlay and index methods to more complicated process-based simulation models. Each method has advantages and limitations, and none is best for all situations. Process-based models at the appropriate scale would be ideal in a perfect world, since they attempt to capture the true physical, chemical, and biological reactions that occur from the surface through the ground water regime. Process-based models, however, have not been demonstrated to be more effective than other techniques. The limitations of process-based models derive from model structure (i.e., lack of knowledge of how to formulate processes mathematically) and, more significantly, from limitations in data availability and quality. Furthermore, limited field experimentation with pesticide simulation models suggests that models based on simplified process representation may be more useful for many vulnerability assessments than more complicated models. Most approaches for ground water vulnerability assessment assume undisturbed surficial deposits with spatially uniform percolation. Preferential flow paths, such as roots and worm holes, cracks, joints, and solution channels,

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty are ignored. Yet these may well be the fundamental pathways affecting vulnerability, providing more direct and rapid paths for contaminants to reach ground water than they would otherwise have. Recent literature suggests that under certain circumstances preferential flow can be a dominant phenomenon (cf., Roth et al. 1991), that it can occur in soils with no apparent structure (cf., Ghodrati and Jury 1990), and that it can channel virtually all of the water and chemical flux through a small portion of the matrix in highly permeable soils that have subsurface lenses in them (cf., Kung 1990a, b). Statistical methods incorporate uncertainty and attempt to explicitly minimize error, but require observations of surrogates for vulnerability (e.g., ground water samples from shallow wells). Using these surrogates, the methods directly derive parameter coefficients instead of assigning weights to attributes based on expert judgment as is done in overlay and index methods. Parameters from simple process-based indices (e.g., travel times) could be used in statistical methods, making for a sort of hybrid approach. However, the results of these methods can only be applied to the geographic areas in which the data were collected to regions where similar factors are associated with the likelihood of ground water contamination. Overlay and index methods have been developed because of limitations in process-based models and because of a lack of monitoring data required for statistical methods. Overlay and index methods are based on assumptions that a few major factors largely control ground water vulnerability and that these factors are known and can be weighted (explicitly in index methods or implicitly in overlay methods). These assumptions have not been demonstrated, particularly with respect to assigning weights to different factors. In reviewing vulnerability assessment methods, it is useful to distinguish between (1) the ability to explain the factors and processes leading to potential contamination of ground water, and (2) the ability to predict likely contamination of ground water at the desired spatial scale. Research over the past two to three decades has contributed significantly to our knowledge and enables us to offer explanations of contamination of ground water. However, our ability to translate this understanding into reliable predictive models is not as sound. Although we can identify many of the factors leading to ground water contamination and construct process-based models that incorporate these parameters, our ability to apply these models in real-world situations is significantly limited. The foregoing remarks suggest that predictions of ground water vulnerability are probabilistic—that is, we may be able to forecast the probability of ground water contamination over a given area, but the level of confidence in such forecasts for any particular location is quite low. Furthermore,

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty it is difficult, if not impossible, to test the validity of these predictions. The challenge of vulnerability assessments resembles the problem of weather forecasting. For example, a forecast of a 70 percent chance of thunder showers in a specific location might be equated to identification of areas with high vulnerability. According to the National Weather Service, such a forecast does not predict rain at any given location or over the entire region, but only a 70 percent probability of rain somewhere (locations unspecified) in the region. It can be argued that vulnerability assessments predict ground water contamination in a relative, not an absolute sense. That is, an assessment only identifies some areas in the region as more or less vulnerable than other areas. Uncertainty is pervasive in both spatial databases and computational schemes; as a result, all vulnerability assessments are inherently uncertain. It may be fairly easy to identify areas where ground water contamination is highly probable but not areas where it is highly improbable. For example, it is relatively easy to determine that ground water in a mature karst aquifer system or in a shallow sand and gravel alluvial aquifer is highly vulnerable to contamination. However, it may be much more difficult to demonstrate that ground water underlying a clay-rich unsaturated zone indeed has low vulnerability to contamination, because many factors difficult to quantify, such as preferential flow paths, may complicate the situation. Moreover, differentiation of areas that are not highly vulnerable to ground water contamination into more subtle distinctions in vulnerability is very difficult. This conclusion may be summarized as the Third Law of Ground Water Vulnerability: The obvious may be obscured and the subtle indistinguishable. Uncertainty in vulnerability assessments needs to be better recognized and revealed in the outputs. Assessment methods coupled with GIS and other sophisticated presentations can suggest greater knowledge than truly exists. Ways in which uncertainty could be better integrated into presentations include identifying the data sites used, developing companion uncertainty maps based on uncertainty analysis of data errors (these maps could be further broken down to show uncertainty associated with different parameters), and presentation of vulnerability maps generated by different methods. Maps produced by different methods, however, should be interpreted with caution as indicators of error because different methods use many of the same data and hence are not independent tests. Vulnerability assessment is an interactive process that should be continually modified and improved using new information. Although assessment methods cannot be validated in the traditional sense, efforts to develop multiple lines of evidence for evaluating these assessments are encouraged.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Ground water quality data, however, should be used with considerable caution to examine differences among vulnerability classes, for a number of reasons. These include uncertainty in the reference location of the production zone of the well used to obtain the sample, uncertainty about the spatial and temporal variations in chemical loadings at the land surface, possible short-circuiting of natural flow paths by wells, and limitations in obtaining representative ground water samples from wells. Several approaches for vulnerability assessments are available, and each has its own strengths, and limitations. All approaches combine uncertainty and should explicitly capture or reflect that uncertainty. Testing and evaluating these approaches is critical to producing a more justifiable, useful, and reasonable assessment. REFERENCES Aller, L., T. Bennett, J.H. Lehr, and R.J. Petty. 1985. DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings. Ada, Oklahoma: U.S. Environmental Protection Agency. Aller, L., T. Bennett, J.H. Lehr, R.J. Petty, and G. Hackett. 1987. DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings. EPA-600/2-87-035. Ada, Oklahoma: U.S. Environmental Protection Agency. Alley, W.M., and P.A. Emery. 1986. Ground water model of the Blue River basin, Nebraska—Twenty years Later. Journal of Hydrology 85:225-249. American Society for Testing and Materials (ASTM). 1984. Standard Practice for Evaluating Environmental Fate Models of Chemicals, 1978-84. Philadelphia, Pennsylvania: American Society for Testing and Materials. Back, R.C., R.R. Romine, and J.L. Hansen. 1984. Rating system for predicting the appearance of temik aldicarb residues in potable water. Environmental Toxicology and Chemistry 3:589-597. Banton, O., and J.P. Villeneuve. 1989. Evaluation of ground water vulnerability to pesticides: A comparison between the quantities. Journal of Contaminant Hydrology 4:285-296. Berg, R.C., and J.P. Kempton. 1988. Stack-Unit Mapping of Geologic Materials in Illinois to a Depth of 15 Meters. Champaign: Illinois State Geological Survey Circular 542. Berryman, D., B. Bobée, D. Cluis, and J. Haemmerli. 1988. Nonparametric approaches for trend detection in water quality time series. Water Resources Bulletin 24(3):545-556. Beven, K. 1991. Modeling preferential Flow: An uncertain future? In Preferential Flow, T.J. Gish and A. Shirmohammadi, eds. Proceedings National Symposium, December 16-17, 1991. St. Joseph, Michigan: American Society of Agricultural Engineers. Bowman, R.S., and R.C. Rice. 1986. Accelerated herbicide leaching resulting from preferential flow phenomenon and its implications for ground water contamination. In Proceedings of the Conference on Southwestern Ground Water Issues, Pheonix, Arizona, October 20-22, 1986. Dublin, Ohio: National Water-Well Association. Brandstetter, A., and B.E. Buxton. 1989. The role of geostatistical, sensitivity and uncertainty analysis in performance assessment. Pp. 89-220 in Geostatistical, Sensitivity, and Uncertainty Methods for Ground Water Flow and Radionuclide Transport Modeling, B.E. Buxton, ed. Conf-870971, Columbus, Ohio: Battelle Press. Burrough, P.A. 1986. Principles of Geographical Information Systems for Land Resource Assessment. Monographs on Soil and Resources Survey No. 12. Oxford, U.K.: Oxford Science Publications, Clarendon Press.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Butters, G.L., W.A. Jury, and F.F. Ernst. 1989. Fieldscale transport of bromide in an unsaturated soil: I. Experimental methodology and results. Water Resources Research 25:1575-1582. Buxton, B.E., ed. 1989. Geostatistical, Sensitivity, and Uncertainty Methods for Ground-Water Flow and Radionuclide Transport Modeling. Conf-870971. Columbus, Ohio: Battelle Press. Carsel, R.F., C.N. Smith, L.A. Mulkey, J.D. Dean, and P. Jowise. 1984. User's Manual for the Pesticide Root Zone Model (PRZM): Release 1. Athens, Georgia: U.S. Environmental Protection Agency, Environmental Research Laboratory. Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988a. Characterizing the uncertainty of pesticide leaching in agricultural soils. Journal of Contaminant Hydrology 2:111-124. Carsel, R.F., R.L. Jones, J.L. Hansen, R.L. Lamb, and M.P. Anderson. 1988b. A simulation procedure for ground water quality assessments of pesticides. Journal of Contaminant Hydrology 2(2):125-138. Chen, H., and A.D. Druliner. 1988. Agricultural Chemical Contamination of Ground Water in Six Areas of the High Plains Aquifer, Nebraska. National Water Summary 1986—Hydrologic Events and Ground-Water Quality . Water-Supply Paper 2325. Reston, Virginia: U.S. Geological Survey. Cherry, J.A. 1983. Piezometers and other permanently installed devices for ground water quality monitoring. Pp. IV-1 to IV-39 in Proc.: Petroleum Association for Conservation of the Canadian Environment, Seminar on Ground water and Petroleum Hydrocarbons Protection, Detection, Restoration. Ottawa. Chrisman, N.R. 1984. The role of quality information in long-term functioning of geographical information systems. Cartographica 21:79-87. Cohen, D.B., C. Fisher, and M.L. Reid. 1986. Ground-water contamination by toxic substances: A California assessment. Pp. 499-529 in Evaluation of Pesticides in Ground Water, W.Y. Garner, R.C. Honeycutt, and H.N. Nigg, eds. ACS Symp. Series 315, Washington, D.C.: American Chemical Society. Dean, J.D., P.S. Huyakorn, A.S. Donigian, Jr., K.A. Voos, R.W. Schanz, Y.J. Meeks, and R.F. Carsel. 1989. Risk of Unsaturated/Saturated Transport and Transformation of Chemical Concentrations (RUSTIC). Volumes I and II. EPA/600/3-89/048a. Athens, Georgia: U.S. Environmental Protection Agency. Dixon, W.J. 1986. Extraneous values. Pp. 83-90 in Methods of Soil Analysis, Part I, Physical and Mineralogical Properties, Second Edition, A. Klute, ed. Agronomy Servies No. 9. Madison, Wisconsin: American Society of Agronomy. Donigian, A.S., Jr., and P.S.C. Rao. 1990. Selection, application, and validation of environmental models. Pp. 577-600 in Proceedings of the International Symposium on Water Quality Modeling of Agricultural Nonpoint Sources, Part 2. ARS-81. Washington, D.C.: USDA Agricultural Research Service. Donigian, A.S., Jr., J.C. Imhoff, and B.R. Bicknell. 1983. Modeling Water Quality and the Effects of Agricultural Best Management Practices in Four Mile Creek, Iowa. Athens, Georgia: U.S. Environmental Protection Agency. Driscoll, F.G. 1986. Ground water and Wells. St. Paul, Minnesota: Johnson Division, UOP. Eisenberg, N.A., L.D. Richerstein, and C. Voss. 1989. Performance assessment, site characterization, and sensitivity and uncertainty methods: Their necessary association for licensing. Pp. 9-38 in Proceedings of the Conference on Geostatistical, Sensitivity, and Uncertainty Methods for Ground-Water Flow and Radionuclide Transport Modeling, B.E. Buxton, ed. Conf-870971. Columbus, Ohio: Battelle Press. Enfield, C.G., R.F. Carsel, S.Z. Cohen, T. Phan, and D.M. Walters. 1982. Approximating pollutant transport to ground water. Ground Water 20(6):711-722.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Freeze, R.A., and J.A. Cherry. 1979. Ground water. Englewood Cliffs, New Jersey: Prentice-Hall. Germann, P.F., ed. 1988. Rapid and far-reaching hydrologic processes in the vadose zone. Journal of Contaminant Hydrology 3:115-380. Ghodrati, M., and W.A. Jury. 1990. A field study using dyes to characterize preferential flow of water. Soil Science Society of America Journal 54:1558-1563. Gibb, J.P., R.M. Schuller, and R.A. Griffin. 1981. Procedures for the Collection of Representative Water Quality Data from Monitoring Wells, Cooperative Ground Water Report 7. Champaign: Illinois State Water Survey. Goodchild, M.F., and O. Dubuc. 1987. A model of error for choroplett maps, with applications to geographic information systems. Pp. 165-172 in Proc. Auto-Carto 8. Falls Church, Virginia: Amer. Congress of Surveying and Mapping. Goodchild, M.F., and W. Min-hua. 1988. Modeling error in raster-based spatial data. Pp. 97-106 in Proc. Third Internal. Symp. Spatial Data Handling. Sydney, Australia. Hamilton, P.A., and J.M. Denver. 1990. Effects of land use and ground-water flow on shallow ground-water quality, Delmarva Peninsula, Delaware, Maryland, and Virginia. Ground Water 28(5):789. Hern, S.C., S.M. Melancon, and J.E. Pollard. 1986. Generic steps on the field validation of vadose zone fate and transport models. In Vadose Zone Modeling of Organic Pollutants, S.C. Hern and S.M. Melancon, eds. Chelsea, Michigan: Lewis Publishers, Inc. Heuvelink, G.B.M., P.A. Burrough, and A. Stein. 1989. Propagation of errors in spatial modeling with GIS. Int. Jour. Geographical Information Systems 3(4):303-322. Hipel, K.W. 1988. Nonparametric approaches to environmental impact assessment. Water Resources Bulletin 24(3):487-492. Holden, L.R., J.A. Graham, R.W. Whitmore, W.J. Alexander, R.W. Pratt, S.F. Liddle, L.L. Piper. 1992. Results of the national alachlor well water survey. Environmental Science and Technology 26(5):935-43. Hoyer, B.E., and G.R. Hallberg. 1991. Ground water Vulnerability Regions of Iowa, Special Map 11. Iowa City: Iowa Department of Natural Resources. Imhoff, J.C., B.R. Bicknell, and A.S. Donigian, Jr. 1983. Preliminary Application of HSPF to the Iowa River Basin to Model Water Quality and the Effects of Agricultural Best Management Practices. EPA Contract No. 68-03-2895. Athens, Georgia: U.S. Environmental Protection Agency. Imhoff, J.C., R.F. Carsel, J.L. Kittle, Jr., and P.R. Hummel. 1990. Data Base Analyzer and Parameter Estimator, DBAPE (User's Manual). EPA/600-3-89-083. Athens, Georgia: Environmental Research Laboratory, U.S. Environmental Protection Agency. Johnston, R.H. 1988. Factors Affecting Ground-Water Quality. National Water Summary 1986: Hydrologic Events and Ground-Water Quality. Water-Supply Paper 2325. Reston, Virginia: U.S. Geological Survey. Jones, R.L., P.S.C. Rao, and A.G. Hornsby. 1983. Fate of aldicarb in florida citrus soils: 2. Model evaluation. Pp. 959-978 in Proceedings of a Conference of Characterization and Monitoring in the Vadose (Unsaturated) Zone, D.M. Nielson, and M. Curl, eds. Dublin, Ohio: National Water Well Association. Jury, W.A., and H. Flüher. 1992. Transport of chemicals through soil: Mechanisms, models, and field applications . Advances in Agronomy 47:141-201. Jury, W.A., and M. Ghodrati. 1989. Overview of organic chemical environmental fate and transport modeling approaches. Pp. 271-304 in Reactions and Movement of Organic Chemicals in Soils, B.L. Sawhney, and K. Brown, eds. Special Publication No. 22. Madison, Wisconsin: Soil Science Society of America. Jury, W.A., and J. Gruber. 1989. A stochastic analysis of the influence of soil and climatic variability on the estimate of pesticide ground water pollution potential. Water Resources Research 25(12):2465-2474.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Jury, W.A., W.F. Spencer, and W.J. Farmer. 1983. Behavior assessment model for trace organics in soil: I. Description of model. Journal of Environmental Quality 12:558-564. Kearl, P.M., N.E. Korte, and T.A. Cronk. 1992. Suggested modifications to ground water sampling procedures based on observations from the colloidal baroscope. Ground Water Monitor Review 12:155-161. Kellogg, R.L., M.S. Maizel, and D.W. Goss. 1992. Agricultural Chemical Use and Ground Water Quality: Where Are the Potential Problems? Washington, D.C. : U.S. Department of Agriculture, Soil Conservation Service. Kempthorne, O., and R.R. Allmaras. 1986. Errors and variability of observations. Pp. 1-32 in Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, Agron. Monograph, No. 9 (2nd edition). Madison, Wisconsin: American Society of Agronomy. Khan, M.A., and T. Liang. 1989. Mapping pesticide contamination potential. Environmental Management 13(2):233-242. Khan, M.A., T. Liang, P.S.C. Rao, R.E. Green. 1986. Use of an interactive computer graphics and mapping system to assess the potential for ground water contamination with pesticides. EOS 67(16):278. Kissel, D.E., O.W. Bidwell, and J.F. Kientz. 1982. Leaching Classes in Kansas Soils. Bulletin No. 641. Manhatten, Kansas: Kansas State University. Kleveno, J.J., K. Loague, and R.E. Green. 1992. Evaluation of a pesticide mobility index: Impact of recharge variation and soil profile heterogeneity. Journal of Contaminant Hydrology 11(1-2):83-99. Knisel, W.G., R.A. Leonard, and F.M. Davis. 1989. GLEAMS User Manual. Tifton, Georgia: Southeast Watershed Research Laboratory. Konikow, L.F., and J.D. Bredehoeft. 1992. Ground-water models cannot be validated. Advances in Water Resources 15:75-83. Kung, K.S. 1990a. Preferential flow in a sandy vadose zone: 1. Field observations. Geoderma 46:51-58. Kung, K.S. 1990b. Preferential flow in a sandy vadose zone: 2. Mechanism and implications. Geoderma 46:59-71. Laskowski, D.A., P.M. Tillotson, D.D. Fontaine, and E.J. Martin. 1990. Probability Modelling. London: Phil. Trans. Royal Society B329:383-389. Leonard, R.A., W.G. Knisel, and D.A. Still. 1987. GLEAMS: Ground water loading effects of agricultural management systems. Trans. Amer. Soc. Agric. Eng. 30:1403-1418. Liang, T., and M.A. Khan. 1986. A natural resource information system for agriculture. Agricultural Systems 21:81-105. Loague, K. 1991. The impact of land use on estimates of pesticide leaching potential: Assessments and uncertainties. Journal of Contaminant Hydrology 8:157-175. Loague, K., and R.E. Green. 1991. Statistical and graphical methods for evaluating solute transport models: Overview and application. Journal of Contaminant Hydrology 7:51-73. Loague, K.M., R.S. Yost, R.E. Green, and T.C. Liang. 1989. Uncertainty in a pesticide leaching assessment for Hawaii. Journal of Contaminant Hydrology 4:139-161. Loague, K., R.E. Green, T.W. Giambelluca, T.C. Liang, and R.S. Yost. 1990. Impact of uncertainty in soil, climatic, and chemical information in a pesticide leaching assessment. Journal of Contaminant Hydrology 5:171-194. McKenna, D.P., and D.A. Keefer. 1991. Potential for Agricultural Chemical Contamination of Aquifers in Illinois. Open File 1991-7R. Champaign: Illinois State Water Survey. McLean, J.E., R.C. Sims, W.J. Doucette, C.R. Caupp, and W.J. Girenney. 1988. Evolution of mobility of pesticides in soil using U.S. EPA methodology. ASCE. Journal of Environmental Engineering 114(3):689-703. Mead, D.A. 1982. Assessing data quality in geographic information systems. Pp. 51-62 in

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Remote Sensing for Resource Management, C.J. Johansen, and J.L. Sanders, eds. Ankeny, Iowa: Soil Conservation Society of America. Meeks, Y.J., and J.D. Dean. 1990. Evaluating ground-water vulnerability to pesticides. Journal of Water Resources Planning and Management 116(5):693-707. Moore, J.S. 1988. SEEPPAGE: A System for Early Evaluation of Pollution Potential of Agricultural Ground Water Environments. Geology Technical Note 5 (Revision 1). Washington, D.C.: U.S. Department of Agriculture, Soil Conservation Service. Moreau, D.H., and L.E. Danielson. 1990. Agricultural Pesticides and Ground Water in North Carolina: Identification of the Most Vulnerable Areas. North Carolina: Water Resources Research Institute of the University of North Carolina, North Carolina State University. National Research Council (NRC). 1990. Ground Water Models: Scientific and Regulatory Applications. Washington, D.C.: National Academy Press. Nelson, D.W., and R.H. Dowdy, eds. 1990. Methods for ground water quality studies. In Proc. National Workshop, Arlington, VA, November 1-3 , 1989. Lincoln, Nebraska: University of Nebraska—Lincoln Press. Nicholls, P.H., R.H. Bromilow, and T.A. Addiscott. 1982a. Measured and simulated behavior of fluometuron, aldoxycarb, and chloride ion in a fallow structured soil. Pesticide Science 12:475-483. Nicholls, P.H., A. Walker, and R.J. Baker. 1982b. Measurement and simulation of the movement and degradation of atrazine and metribuzin in a fallow soil. Pesticide Science 12:484-494. Nofziger, D.L., and A.G. Hornsby. 1986. A microcomputer-based management tool for chemical movement. Soil. App. Agr. Res. 1:50-56. Pedroli, B. 1990. Classification of Shallow ground water types in a dutch covers and landscape. Journal of Hydrology 115:361-375. Pennell, K.D., A.G. Hornsby, R.E. Jessup, and P.S.C. Rao. 1990. Evaluation of five simulation models for predicting aldicarb and bromide behavior under field conditions. Water Resources Research 26(11):2679-2693. Pettyjohn, W.A., M. Savoca, and D. Self. 1991. Regional Assessment of Aquifer Vulnerability and Sensitivity in the Conterminous United States . Report EPA-600/2-91/043. Ada, Oklahoma: U.S. Environmental Protection Agency. Plummer, L.N., R.L. Michel, E.M. Thurman, and P.D. Glynn. 1993. Environmental tracers for age-dating young ground water. Pp. 255-294 in Regional Ground-Water Quality, W.M. Alley, ed. New York: Van Nostrand Reinhold. Popper, K. 1959. The Logic of Scientific Discovery. New York: Harper and Row. Puls, R. W., and M.J. Barcelona. 1989a. Filtration of ground water samples for metals analysis. Hazardous Waste & Hazardous Materials 6(4):385-393. Puls, R.W., and M.J. Barcelona. 1989b. Ground Water Sampling for Metals Analysis. Superfund Ground Water issue. U.S. Environmental Protection Agency. Puls, R.W., and R.M. Powell. 1992. Acquisition of representative ground water quality samples for metals. Ground Water Monitoring Reviews 12:167-176. Rao, P.S.C., A.G. Hornsby, and R.E. Jessup. 1985. Indices for Ranking the Potential for Pesticide Contamination of Ground water . Soil Crop Science Society Florida Proceedings 44:1-8. Rawls, W.J., and D.L. Brakensiek. 1985. Prediction of Soil Water Properties for Hydrological Modeling. In Proc. Symposium of Committee of Watershed Management, Irrigation and Drainage Div., ASCE Convention, Denver, CO. Riley, J.A., R.K. Steinhorst, G.V. Winter, and R.E. Williams. 1990. Statistical analysis of the hydrochemistry of ground waters in Columbia River basalts. Journal of Hydrology 119:245-262.

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Robbins, G.A. 1989. Influence of using purged and partially penetrating monitoring wells on contaminant detection, mapping, and modeling. Ground Water 27(2):155-162. Robbins, G.A., and J.M. Martin-Hayden. 1991. Mass balance evaluation of monitoring well purging: I. Theoretical models and implications for representative sampling. Journal of Contaminant Hydrology 8:203-24. Robbins, G.A., R.D. Bristol, J.M. Hayden, and J.D. Stuart. 1989. Mass continuity and distribution implications for collection of representative ground water samples from monitoring wells. Pp. 125-140 in Proceedings of the Conference on Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Restoration. Dublin, Ohio: National Water Well Association. Robin, M.J.L., and R.W. Gillham. 1987. Field evaluation of well purging procedures. Ground Water Monitoring Review 7:85-93. Roth, K., W.A. Jury, H. Flüher, and W. Attinger. 1991. Transport of chloride through an unsaturated field soil. Water Resources Research 27(10):2533-2541. Rupert, M., T. Dace, M. Maupin, and B. Wicherski. 1991. Ground Water Vulnerability Assessment: Snake River Plain, Southern Idaho. Boise: Idaho Department of Health and Welfare. Ryan, J.N., and P.M. Gschwend. 1990. Colloid mobilization in two Atlantic coastal plain aquifers: Field studies. Water Resources Research 26:307-322. Sacha, L., D. Fleming, and H. Wysocki. 1987. Survey of Pesticides in Selected Areas Having Vulnerable Ground Waters in Washington State. EPA/910/9-87/169. Seattle, Washington: U.S. Environmental Protection Agency, Region X. Seyhan, E., A.A. van de Griend, and G.B. Engelen. 1985. Multivariate analysis and interpretation of the Hydrochemistry of a Dolomitic Reef Aquifer, Northern Italy. Water Resources Research 21(7):1010-1024. Small, M.J., and J.R. Mular. 1987. Long-term pollutant degradation in the unsaturated zone with stochastic rainfall infiltration. Water Resources Research 23:2246-2256. Smith C.N., R.S. Parrish, R.F. Carsel, A.S. Donigian, Jr., and J.M. Cheplick. 1988. Validation Status of Pesticide Leaching and Ground water Transport Model. Athens, Georgia: U.S. Environmental Protection Agency, Environmental Research Laboratory. Steenhuis, T.S., S. Pacenka, and K.S. Porter. 1987. MOUSE: A management model for evaluation ground water contamination from diffuse surface sources aided by computer graphics. Appl. Agr. Res. 2:277-289. Teso, R.R., T. Younglove, M.R. Peterson, D.L. Sheeks, III, and R.E. Gallavan. 1988. Soil taxonomy and surveys: Classification of areal sensitivity to pesticide contamination of ground water. Journal of Soil and Water Conservation 43(4):348-352. U.S. Army Corps of Engineers. 1988. GRASS, Geographic Resource Analysis Support System Version 3.0. Champaign, Illinois: Construction Engineering Research Laboratory. U.S. Department of Agriculture (USDA). 1985. User Manual for Interactive Soils Data Bases: National Soil Survey Area Data Base, Soil Interpretations Record Data Base and Plant Name Data Base. Fort Collins, Colorado: USDA, Soil Conservation Service. U.S. Department of Agriculture (USDA). 1986. Urban Hydrology for Small Watersheds, TR-55. USDA, Soil Conservation Service. U.S. Environmental Protection Agency (EPA). 1982. Exposure modeling committee report: Testing for the field applicability of chemical exposure models. In Proc. Workshop on Field Applicability Testing. Athens, Georgia: U.S. EPA. U.S. Environmental Protection Agency (EPA). 1989. Resolution on Use of Mathematical Models by EPA for Regulatory Assessment and Decision-Making. Prepared by the Environmental Engineering Committee of the Science Advisory Board. EPA-SAB-EEC-89012. Washington, D.C.: U.S. Environmental Protection Agency. U.S. Environmental Protection Agency (EPA). 1992a. A Review of Methods for Assessing

OCR for page 42
Ground Water Vulnerability Assessment: Contamination Potential Under Conditions of Uncertainty Aquifer Sensitivity and Ground-Water Vulnerability to Pesticides. Contract No. 68-C0-0083. Raleigh, North Carolina: Geraghty & Miller, Inc. U.S. Environmental Protection Agency (EPA). 1992b. Another Look: National Survey of Pesticides in Drinking Water Wells Phase II Report. Washington, D.C.: U.S. Environmental Protection Agency. van Genuchten, M.T. 1978. Calculating the Unsaturated Hydraulic Conductivity with a New Closed-Form Analytical Model. 78-WR-08. Princeton, New Jersey: Water Resources Program, Department of Civil Engineering, Princeton University. Vieux, B.E., and Y.T. Kang. 1990. GRASS Waterworks: A GIS Toolbox for Watershed Hydrologic Modeling. Proceedings of Application of GIS, Simulation Models, and Knowledge-Based Systems for Land Use Management. November 12-14, 1990. Blacksburg: Virginia Polytechnic and State University. Villeneuve, J., O. Banton, P. Lafrance, and P.G.C. Cambell. 1987. A new model for the evaluation of ground water vulnerability to non-point contamination by pesticides. Pp. 1097-1109 in Vulnerability of Soil and Ground water to Pollutants, W. van Duijvenbooden and H.G. van Waegeningh, eds. The Hague, Netherlands: TNO Committee on Hydrological Research., National Institute of Public Health and Environmental Hygiene. Wagenet, R.J., and J.L. Hutson. 1987. LEACHM: A Finite-Difference Model for Simulating Water, Salt, and Pesticide Movement in the Plant Root Zone, Continuum 2. Ithaca: New York State Resources Institute, Cornell University. Wagenet, R.J., and P.S.C. Rao. 1990. Modeling pesticide fate in soil. Pp. 357-399 in Pesticides in the Soil Environment, SSSA Book Series No. 2, H.H. Cheng, ed. Madison, Wisconsin: Soil Science Society of America. Wisconsin Department of Natural Resources, and Wisconsin Geological and Natural History Survey. 1987. Ground water Contamination Susceptibility in Wisconsin. Madison: Wisconsin Geological and Natural History Survey.